The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Towards a statistical test for functional connectivity dynamics
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
On spurious and real fluctuations of dynamic functional connectivity during rest
Leonardi, N., & Van De Ville, D. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.007 · Cited by 828
Time-resolved resting-state brain networks
Zalesky, A., Fornito, A., Cocchi, L., Gollo, L. L., & Breakspear, M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400181111 · Cited by 753
Temporally-independent functional modes of spontaneous brain activity
Smith, S. M., Miller, K. L., Moeller, S., Xu, J., Auerbach, E. J., Woolrich, M. W., Beckmann, C. F., Jenkinson, M., Andersson, J., Glasser, M. F., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121329109 · Cited by 702
DEM: A variational treatment of dynamic systems
Friston, K. J., Trujillo-Barreto, N., & Daunizeau, J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.054 · Cited by 278 · cited 1×
“Model inversion using variational techniques can compliment this approach by allowing one to compare among various sets of assumptions, particularly since these inversion methods are now suitable for complex, nonlinear systems (Daunizeau et al., 2009; Friston et al., 2008).”
Spectral characteristics of resting state networks
Niazy, R. K., Xie, J., Miller, K., Beckmann, C. F., & Smith, S. M. (2011) · Progress in brain research · doi:10.1016/b978-0-444-53839-0.00017-x · Cited by 175
Cited by
Dynamic models of large-scale brain activity
Breakspear, M. (2017) · Nature Neuroscience · doi:10.1038/nn.4497 · Cited by 1,239
Self-citationQuestions and controversies in the study of time-varying functional connectivity in resting fMRI
Lurie, D. J., Kessler, D., Bassett, D. S., Betzel, R. F., Breakspear, M., Kheilholz, S., Kucyi, A., Liégeois, R., Lindquist, M. A., McIntosh, A. R., et al. (2020) · Network Neuroscience · doi:10.1162/netn_a_00116 · Cited by 648
Self-citationOn the stability of BOLD fMRI correlations
Laumann, T. O., Snyder, A. Z., Mitra, A., Gordon, E. M., Gratton, C., Adeyemo, B., Gilmore, A. W., Nelson, S. M., Berg, J. J., Greene, D. J., et al. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw265 · Cited by 516
Betzel, R. F., Fukushima, M., He, Y., Zuo, X.-N., & Sporns, O. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.12.001 · Cited by 249
“Despite its rapid adoption, the methodological pitfalls of using such an approach to obtain estimates of dynamic functional connectivity are not fully understood (Hlinka and Hadrava, 2015; Zalesky and Breakspear, 2015; Leonardi andVanDeVille, 2015).”
BackgroundResultInfluentialFrom maps to multi-dimensional network mechanisms of mental disorders
Braun, U., Schaefer, A., Betzel, R. F., Tost, H., Meyer-Lindenberg, A., & Bassett, D. S. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.007 · Cited by 177
Metadata
- Authors
- Zalesky, A., & Breakspear, M.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2015-07
- Volume
- 114
- Pages
- 466-470
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2011611054
- Cited by
- 257
- References
- 6
- FWCI
- 16.41
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
